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One of the major roadblocks that an organization faces is PLM complexity. PLM users need time to adapt to a new system or feature and require constant and quick real-time support in case of difficulties. Conventional means of emailing/ticketing systems take a lot of time and may discourage users as well as result in costly business hours.
One way to solve the problem is automation where PLM users won’t get into the hassle of using their valuable time in raising tickets or waiting in the ticketing queue to get their errors resolved. What users need today is a more personalized tailor-made approach and, what better way than a CHATBOT – an informal and immediate way of contact to service these users. Chatbots are everywhere, being the fastest growing communication channel, with a 92% increase in usage since 2019.
These voice assistants are part of the customer support system for their respective brands, solving queries in a direct, real-time, and personalized manner. But, even these chatbots have faced their share of problems. If faced with a unique query, it is often observed that they take time to resolve the query and fail to transfer to human support, hence losing the user’s valuable time.
This chatbot pain point was confirmed in a survey that we undertook a few weeks ago. The majority of the respondents stated that they chose to speak to human support after the chatbots were unable to understand the problem and solve the query.
Users want fast and efficient support that can be achieved when chatbots are proactive and provide real-time support. It was reiterated by the majority of survey respondents who said that they want the chatbots to be intelligent and have self-learning ability. Also, they stated that chatbots should not waste time and transfer to human support immediately if they fail to solve the problem.
An AI-powered Chatbot has machine learning capabilities, that will have them assess if they can handle a request. In case they are unable to process the request, these bots can call for backup, transferring to human support to take over the request. Also, if the human support observes that the bot’s answer is closer to resolving the request, then they can signal the same to the bot. Once reviewed and approved by a human, the chatbot can continue interacting with the user.
When harnessed right, these AI-enabled chatbots are a terrific asset for PLM support, reducing support from multiple clicks to a single click. They can be deployed to aid PLM users by clarifying steps, giving useful links, and bridging the gap between user-specific training and independent user working.
You can improve your design release process, workflows and overcome obstacles in PLM implementation and support among other advantages. The support team can also concentrate on more complicated and tedious support issues while a smart chatbot solves other queries. Also, with integration to data analytics, chatbots can monitor user actions and suggest necessary steps and user-specific guidance.
We at PLM Nordic have done extensive research and developed a PLM-specific SMARTBOT.
1. Accuracy – thanks to our AI-based training algorithms developed for PLM applications.
2. When unable to answer, auto-transfer to human support and learn from the conversation.
3. You can train SMARTBOT easily periodically based on your documents like support logs, emails, wiki pages.
4. Using data analytics and user intelligence to improve the context in answers.
5. Push User-specific guidance and training based on behavior and usage.
And many more features…
If you are interested in getting a glimpse of our SMARTBOT and have an exclusive look at its advanced features that will benefit PLM user engagement and the overall PLM program, register for our webinar here or book a demo with us here https://calendly.com/plmnordic.
1 Comment
Nice article. I did research on the users who wanted to use a mobile application-like product for PLM. The usability of the software over popular OS like Android, and IOS is very limited to certain major providers only. it could be a game changer to build a common mobile friendly app that fit in requirements of agility.